Economic Management Journal February 2016, Volume 5, Issue 1, PP.19-27
Research on the Influencing Factors of Environmental Information Disclosure in Thermal Power Enterprises* Liping Yan †
School of Economy and Management, North China Electric Power University, Baoding, Hebei Province 071051, P.R.China †
Email: zfyfylzzkj@163.com
Abstract Based on the data of 2014 annual report, this paper takes 46 thermal power listing corporations as the sample, uses multiple linear regression analysis to analyze the influencing factors of environmental information disclosure in the thermal power corporations in China. Study found that Chinese thermal power listed companies' environmental information disclosure level disparity, overall disclosure level is not high at the present stage. Company size, asset liability ratio, government compensation and social responsibility report preparation have a positive correlation with environmental information disclosure index and have a significant effect on it. Keywords: Thermal Power Enterprise; Environmental Information; Information Disclosure
1 INTRODUCTION The disclosure of environmental information refers to the company overt the impact that all kinds of activities on environment to the public. This is a manifestation of corporate social responsibility. After 1990s, with the enhancement of environmental protection awareness of the government and the public, companies have expanded their environmental information in the annual report, and even the prepared separate environmental reports. Western scholars have carried out a thorough study on the environmental information disclosure by using the standard analysis and empirical analysis. Chinese scholars’ researches are mainly based on the normative analysis, the empirical analysis is less and the strength is not enough. Therefore, this paper takes thermal power enterprises as the research sample, analyzes the factors that influence the environmental information disclosure, and puts forward the countermeasures and suggestions of improving the environmental information disclosure of listing Corporation.
2 VARIABLE SETTING AND RESEARCH HYPOTHESIS 2.1 Dependent Variable Setting This paper takes environmental information disclosure level index(EDI) as independent variable, scores and sums 46 listed companies environmental information disclosure item by item in 2014 annual report using international popular aggregating method, and obtains sample companies' environmental information disclosure index, namely dependent variable Y. Specific items are shown in table 1.
2.2 Independent Variable Setting This paper chooses 11 variables as the independent variables of environmental information disclosure level, and puts forward the corresponding hypothesis combined with the characteristics of thermal power industry. Specific * Project supported by the Fundamental Research Funds for the Central Universities (13MS114) and Hebei province research project on people's livelihood (201501516).
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variables description is shown in table 2. TABLE 1 ENVIRONMENTAL INFORMATION DISCLOSURE RATING SCALE Disclosure Items
Qualitative Description
Quantitative Description
Optimal Value
Environmental protection ideas, guidelines and objectives
2
Waste disposal measures
2
Settings of environmental protection department and system
2
Impact that national environmental protection policies, industry characteristics on the company
2
ISO14000 environmental system certification
2
Implementation of environmental regulations
2
Energy saving effect
3
Pollutant reduction effect
3
Environmental protection investment (equipment, personnel, etc.)
3
Environmental litigation fines, compensation and reward
3
Significant impact or public complaints to the surrounding environment
3
Green fees, sewage charges, resource tax and other environmental costs
3
Environmental Grants, subsidies and tax relief
3
Scoring Criteria
Detail description 2 Simple description 1 No description 0
Detail description 3 Simple description 2 Qualitative Simple description 1 No description 0
TABLE 2 INDEPENDENT VARIABLES’ DESCRIPTION Variable
Symbol
Description
Company Size
X1
X1=LN(Total ending assets)
Asset Liability Ratio
X2
X2=(Total liability/Total assets)×100%
Net Asset Profit Ratio
X3
X3=(Net profit /Total assets)×100%
Outstanding Shares Proportion
X4
X4=(Outstanding shares/Total shares)×100%
Foreign Shares Proportion
X5
X5=(Foreign shares/Total shares))×100%
Independent Director Ratio
X6
X6=Number of independent directors/ Number of directors
Government environmental protection Grant and Award
X7
The value is 1 if obtained the environmental award in the period of annual report, otherwise it is 0.
Regional Differences
X8
The value is 0 in the eastern region, the value is 1 in the middle region; and the value is 2 in the western region.
ISO14000 Environmental System Certification
X9
The value is 1 gained the ISO14000 environment system certification in the period of annual report, otherwise it is 0.
Social Responsibility Report
X10
The value is 1 published the 2014 annual social responsibility report , otherwise it is 0.
Listing Exchange
X11
The value is 1 listed in Shanghai Stock Exchange , otherwise it is 0.
2.3 Research Hypothesis H1: The greater the listing corporation, the higher the level of environmental information disclosure. Larger companies tend to attract a large number of investors, suppliers, customers, investment analysts, etc., it is bound to be required to disclose its information. In order to improve the company's image, the larger company has the power and the ability to disclose more environmental information. The author uses the natural logarithm of total - 20 http://www.emj-journal.org/
assets amount as an index to measure the level of environmental information disclosure. H 2: The higher the Asset Liability Ratio, the higher the level of environmental information disclosure. From the perspective of creditors, the higher the company's Asset Liability Ratio, the lower the safety factor of the loan. The creditor may require companies to disclose more information (including information on environmental factors, environmental system certification, compliance with environmental regulations, etc.) in order to ensure their own interests. From the perspective of company, it will be willing to disclose more environmental information to get the trust of creditors. H3: The higher the profitability, the higher the level of environmental information disclosure. The stronger the company's profitability, the more disclosure of information, that not only can get the trust of investors and stakeholders, but also convey the positive information of corporate social responsibility. The author chooses the Net Asset Profit Ratio as the indicator of the company's profitability. H4: The higher the Outstanding Shares Proportion, the higher the level of environmental information disclosure. The company with Large Outstanding Shares Proportion will be more willing to disclose more environmental information in order to obtain the trust and support of shareholders. H5: The greater the Foreign Shares Proportion, the higher the level of environmental information disclosure. Economic globalization has intensified the international competition of enterprises. Many enterprises need to enhance the international competitiveness, so they have to disclose more environmental information to attract foreign investment. H6: The greater the Independent Director Ratio, the higher the level of environmental information disclosure. Independent director is a director who is independent of the company's shareholders, not in the company, and has no significant business or professional contacts with the company or company's management. Independent director's background and academic degree make them more likely to represent the interests of investors, which are more conducive to the disclosure of environmental information. H7: The more the government environmental protection grants or award, the higher the level of environmental information disclosure. Only enterprises are more proactive to disclose environmental information, they can obtain government grants or award. The author assumes that the variable is a dummy variable, if the listing corporation got the government environmental grants or award in the period of annual report, the value of the variable is 1, otherwise is 0. H8: The more developed areas of the listing corporation, the higher the level of environmental information disclosure. Based on the registered address of the listing corporation, the author assumes that the variable is a dummy variable. If the listing corporation registered in the eastern region, the value is 0. If the listing corporation registered in the middle region, the value is 1. If the listing corporation registered in the western region, the value is 2. H9: Listing corporation passed the ISO14000 environmental management system certification, the level of environmental information disclosure is more higher. ISO14000 environmental management system is to regulate the enterprise and social organizations’ environmental behavior in order to achieve the purpose of saving resources, reducing environmental pollution, improving environmental quality, promoting economic sustainable and healthy development. The author assumes that the variable is a dummy variable, if the listing Corporation passed the ISO14000 environmental system certification in the period of annual report, the value of the variable is 1, otherwise the value is 0. H10: Listed corporation prepares social responsibility report, the level of environmental information disclosure is more higher. - 21 http://www.emj-journal.org/
The preparation of social responsibility report is an important means to enhance the corporate image. The variable is a dummy variable, if the listing corporation released the 2014 annual social responsibility report, the value is 1, otherwise it is 0. H 11: The company listed in the Shanghai stock exchange, the level of environmental disclosure is more higher. Shanghai stock exchange’s system is more perfect, the listing corporation will have more constraints, including the system of environmental information disclosure. The variable is a dummy variable, if the corporation listed in the Shanghai stock exchange, the value is 1, otherwise it is 0.
3 SAMPLE SELECTION AND MODEL CONSTRUCTION 3.1 Sample Selection The disclosure of environmental information in heavy pollution industry listing corporation can be analyzed, which can represent the overall level of environmental information disclosure in China's listing corporation. This paper selects 46 thermal power listing corporations as research sample, including 24 corporations in the Shanghai Stock Exchange, 22 corporations in Shenzhen Stock Exchange. The sample is shown in Table 3. TABLE 3 RESEARCH SAMPLES Serial Number
Stock Code
Corporate Name
Serial Number
Stock Code
Corporate Name
1
600011
HNP
24
600995
WSDL
2
600021
SEP
25
000690
BAOLIHUA NEW ENERGY
3
600023
ZZEPC
26
000695
TJBE
4
600027
HDPI
27
000966
CYDL
5
600098
GDG
28
000958
DONGFANG ENERGY
6
600101
MXEP
29
000791
GEPIC
7
600310
GDEP
30
000899
JCGNCL
8
600396
JINSHAN ENERGY
31
000883
HEGC
9
600452
FULING POWER
32
000722
HUNAN DEVELOPMENT
10
600505
XCEP
33
000692
HUITIAN THERMAL POWER
11
600509
TIANFU ENERGY
34
000875
JPSC
12
600578
BJP
35
000600
JOINTO ENERGY
13
600674
SCTE
36
000993
MDEP
14
600719
DTPC
37
000601
SHAONENG GROUP
15
600726
HDECL
38
000037
NANSHAN POWER
16
600744
DHEP
39
000027
SHENZHEN ENERGY
17
600758
HYNY
40
000543
WENERGY
18
600780
TEC
41
000720
XN&TS
19
600795
GDPD
42
001896
YNHC
20
600863
NMHD
43
000539
GED
21
600886
SDIC POWER
44
000767
ZHANGZE POWER
22
600969
CHENDIAN INTERNATIONAL
45
000531
HENGYUN
23
600982
NBTP
46
002039
QYDL
Note: The sample data comes from Http://www.cninfo.com.cn - 22 http://www.emj-journal.org/
3.2 Construction of Multiple Regression Model This paper studies on the significant factors that impact behavior of environmental information disclosure by using the method of multiple linear regression analysis and SPSS software to carry out regression analysis. Multiple regression model is established as follows: Y=β0 + β1X1 + β2X2+ β3X3+ β4X4+ β5X5 + β6X6 + β7X7 + β8X8+ β9X9+ β10X10+ β11X11+ε β0 is a constant which is independent of all the factors. β1～β11 are regression coefficients, which means the change amount of dependent variable when the independent variables change in each unit. ε is a random disturbance.
4 EMPIRICAL ANALYSIS 4.1 Descriptive Statistical Analysis 1)
Descriptive Statistical Analysis of Continuous Independent Variables TABLE 4 DESCRIPTIVE STATISTICAL ANALYSIS OF CONTINUOUS INDEPENDENT VARIABLES Variable
Maximum Value
Minimum Value
Mean
Standard Deviation
Company Size
7.81
0.63
4.47
1.5838
Asset Liability Ratio
0.9085
0.1717
0.6034
0.1846
Net Asset Profit Ratio
3.1530
-0.2678
0.1646
0.4667
Outstanding Shares Proportion
1.0000
0.0668
0.7965
0.2564
Foreign Shares Proportion
0.4377
0.0000
0.0284
0.0868
Independent Director Proportion
0.5000
0.2308
0.3574
0.0592
According to the results shown in Table 4, the maximum value of Net Asset Profit Ratio is 3.1530, the minimum value is -0.2678, the mean is 0.1646, the standard deviation is 0.4667. This shows that there is big difference in the profitability. The mean of outstanding shares proportion is only 0.7965, which indicates that there are still a part of non-outstanding shares in the listing corporation. Non-outstanding shares cannot make equity share, therefore, the governance structure of the listing corporation needs to be further improved in China. The maximum value of foreign shares proportion is 0.4377, the minimum value is 0, the mean is 0.0284. This shows that the proportion of foreign investment is low in China's thermal power listed companies. The mean of proportion of independent directors is 0.3574, which means that the proportion of the independent directors meets the requirements of China Securities Regulatory Commission(CSRC). However, the minimum value is 0.2308, which indicates that the system of the independent director of some enterprises needs to be further improved. 2)
Descriptive Statistical Analysis of Dummy Independent Variables TABLE 5 DESCRIPTIVE STATISTICAL ANALYSIS OF DUMMY INDEPENDENT VARIABLES Variable
Maximum Value
Minimum Value
Mean
Standard Deviation
Government environmental protection Grant and Award
1
0
0.83
0.3832
Regional Differences
2
0
0.74
0.8010
ISO14000 Certification
1
0
0.02
0.1474
Social Responsibility Report
1
0
0.46
0.5036
Listing Exchange
1
0
0.52
0.5050
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The mean of government environmental protection grant and award is 0.83, which means 83% of enterprises have obtained the government's grand and award. It reflects the Chinese government attaches great importance to environmental protection of the thermal power industry. The mean of ISO14000 certification is 0.02, which shows that only 2% of enterprises have achieved ISO14000 series certification. It means that it is almost blank in ISO14000 series certification in the thermal power industry in China, and far from the international advanced level. The mean of the social responsibility report is 0.46, which shows that 46% of the enterprises have prepared a separate social responsibility report, there are still more than 50% of the enterprises that do not compile. This shows that thermal power enterprises’ management has relatively poor initiative to disclose the environmental information and doesn’t not pay full attention to the social responsibility report. 3)
Descriptive Statistical Analysis of Dependent Variable TABLE 6 DESCRIPTIVE STATISTICAL ANALYSIS OF DEPENDENT VARIABLE Variable
Maximum Value
Minimum Value
Mean
Standard Deviation
EDI
31.00
1.00
14.61
7.9428
TABLE 7 EDI DISTRIBUTION STATISTICS Distribution Interval
EDI ≥30
15≤ EDI <30
0≤ EDI <15
Statistics
1
20
25
%
2.17
43.48
54.35
From table 1, we can see that the optimal value of EDI is 33. According to table 6, the maximum value of EDI is 31, the minimum value is 1, the mean value is 14.61. According to table 7, that 25 enterprises’ value are below the mean value, accounting for 54.35% of the total samples. This data shows that the whole level of environmental information disclosure of the thermal power is not high, and there is obvious difference among thermal power enterprises.
4.2 Significance Test on Model According to table 10, R=0.756, which shows that there is a relatively good correlation between independent variables and dependent variables. The adjusted R2 can better reflect the model's Goodness of Fit, and the adjusted R2=0.531 in the model shows that the independent variables have a large effect on the dependent variable, that is to say, 53.1% of the variation of dependent variable is caused by the independent variables. It also shows that there are other independent variables that have not been considered. In the analysis of variance, F-measure is 13.714, which passes the hypothesis test of the significance level is 0.01. Furthermore, the SIG value is 0, which rejects the hypothesis that the regression coefficient is zero. Hence the regression equation is meaningful.
4.3 Correlation Analysis In order to eliminate the influence of the correlation between the independent variables on the regression results, it is necessary to test the correlation between the independent variables before regression analysis. The Pearson correlation coefficient between the variables is shown in table 8. As shown in Table 8, it is significantly positively related between EDI and company size, Asset Liability Ratio, social responsibility report in the level of 1%, and the government environmental protection grants in the level of 0.5%, which provides a basis for multiple regression analysis. However, the correlation between the other independent variables and EDI is not significant. Meanwhile, there is a significant correlation between some independent variables, such as Asset Liability Ratio and Net Asset Profit Ratio, government environmental protection grants and independent director proportion or regional differences, social responsibility report and the listed exchange. So we can not rule out the possibility of multiple collinear. - 24 http://www.emj-journal.org/
TABLE 8 CORRELATION MATRIX X1
X2
X1
1
X2
.181
X3
X4
X5
X6
-.004
-.100
-.078
-.219
1 -.385**
-.028
.261
1
.041
.181
X7
X8
X9
X10
X11
Y
.203
-.249
-.077
.233
.203
.463**
-.151
.144
-.137
.022
-.122
-.138
.444**
-.147
.102
.009
.248
.027
.154
.096
-.049
X3
-.004 -.385**
X4
-.100
-.028
.041
1
.087
.085
.065
.008
-.201
.232
.073
-.040
X5
-.078
.261
-.147
.087
1
-.141
.148
-.231
-.048
.130
.011
.157
X6
-.219
-.151
.102
.085
-.141
1
-.295*
.162
-.061
-.218
.018
-.285
X7
.203
.144
.009
.065
.148
-.295*
1
-.296*
.068
-.040
.020
.342*
X8
-.249
-.137
.248
.008
-.231
.162
-.296*
1
.049
-.084
.124
-.271
X9
-.077
.022
.027
-.201
-.048
-.061
.068
.049
1
-.137
-.156
-.031
X10
.233
-.122
.154
.232
.130
-.218
-.040
-.084
-.137
1
.441**
.423**
X11
.203
-.138
.096
.073
.011
.018
.020
.124
-.156
.441**
1
.069
.463**
.444**
-.049
-.040
.157
-.285
.342*
-.271
-.031
.423**
.069
1
Y
In general, the criterion for the multiple collinear is that when the independent variable is regressed, the correlation coefficient between the independent variables is greater than (including) 0.5. As shown in Table 8, the correlation coefficients of the independent variables in this paper are less than 0.5, the maximum coefficient is 0.441. Therefore, it can be preliminarily judged that the possibility of multiple linear is small. However, in order to ensure that the results of multiple regressions have significant economic significance, this paper further examines whether there is a multiple collinear between the variables.
4.4 Multiple Collinear Test TABLE 9 MULTIPLE COLLINEAR DIAGNOSIS RESULTS Variable
Tolerance
VIF
X2
.945
1.058
X10
.972
1.029
X1
.891
1.122
X7
.907
1.103
It is usually considered that it has serious multiple collinear between the independent variables and the others when Tolerance of an independent variable is less than 0.1, or VIF is over 10. When VIF approaches to 1, and Tolerance is more than 0.5, it can be considered the effect of the multiple collinear among the variables is very small. As shown in Table 9, VIF of the model is greater than 0 and less than 10, the maximum is 1.122. Tolerance is more than 0.5, and the lowest tolerance level is 0.891. In addition, the Std. Error is relatively small. Lower VIF, Std. Error and higher Tolerance indicate that the sample number is consistent with the basic hypothesis and requirement of multiple regression. So there is no multiple linear problem between the independent variables. The data can be used for multiple linear regression analysis. - 25 http://www.emj-journal.org/
4.5 Regression Results Analysis TABLE 10 REGRESSION RESULTS Model
4
Unstandardized Coefficients B
Std. Error
(Constant)
-10.300
3.738
X2
0.200
.050
X10
7.311
X1 X7
Standardized Coefficients t
SIG.
-2.755
.009
.425
4.043
.000
1.634
.464
4.474
.000
1.285
.543
.256
2.367
.023
4.696
2.223
.227
2.112
.041
F=13.714
SIG=0.00
Beta
R=0.756
Adjusted R2=0.531
B represents the regression coefficient, T value is the result of t test of regression coefficient, SIG value represents the significance of t test in table 10. From the last column of table 10, the SIG value is less than 0.05, which indicates that the regression coefficient of each independent variable passes the significance test, the independent variables X1, X2, X7, and X10 can effectively predict the change of Y. Other variables affect the EDI, but they do not pass the significance test, which indicates that these factors have no significant effect on the EDI, can not effectively explain the change of Y. Therefore, the final regression equation is: Y=1.285X1＋0.2X2＋4.696X7＋7.311X10－10.3 Namely: the company size increases per unit, the level of environmental information disclosure will increase 1.285 units; asset liability rate increases per unit, the level of environmental information disclosure will be increased by 0.2 units; the enterprises’ environmental information disclosure level that obtain governmental environmental protection grand will be improved by 4.696 units; the enterprises; environmental information disclosure level that release social responsibility report will be improved by 7.311 units.
5 CONCLUSION This paper takes China's thermal power listing corporation as the research object, uses the regress analysis method to analyze the influence factors on environmental information disclosure. Through the research, the author draws up the following conclusions: The overall environmental information disclosure level is low. Research data shows that the average value of EDI of thermal power listing corporation in 2014 is 14.61, the highest value is 31, but the lowest value is only 1. The difference is relatively large, which shows that the level of environmental information disclosure of the thermal power listing corporation in China is different, the overall disclosure level is not high. Environmental information disclosure level is affected by company size, asset liability ratio, government compensation and social responsibility report obviously. According to the empirical research, it has a positive and significant correlation between company size, Asset Liability Ratio, government compensation and social responsibility report preparation and EDI. These factors, such as enterprise scale, the concern of creditors, the government's encouragement, the promotion of industry associations and other factors can promote the listing corporation to disclose environmental information.
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AUTHORS Liping Yan was born in March 1980, obtained a master's degree in management from Agricultural University of Hebei in 2005.The author’s major field of study is
Accounting and Financial Management. She is now working in North China Electric Power University in China.
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